wangyinfeng
commented
5 years ago 最终IaaS的业务类似于水电，需要依靠规模取胜，且随着规模的增长，在一个区域内形成技术，价格双垄断，后来者的机会越来越小，类似于当前的能源巨头，几百年来座位变化不会太大，除非核聚变商用，颠覆者出现。
依靠规模取胜的业务，对成本是必然敏感的，成不了高达上的行业，难以容忍试错和失败，判断不会是一个充满机会的行业。最终的IaaS提供商没有几家，行业发展会趋于平稳，在其中的机会也会逐渐丧失。开花的还是上层业务，解决上云痛点问题，提供多云部署方案，以及针对行业的SaaS业务。
When a Cloud is made available in a pay-as-you-go manner to the general public, we call it a Public Cloud;
Similarly, the advantages of the economy of scale and statistical multiplexing may ultimately lead to a handful of Cloud Computing providers who can amortize the cost of their large datacenters over the products of many “datacenter-less” companies. ---- like fab-less
Therefore, a necessary but not sufficient condition for a company to become a Cloud Computing provider is that it must have existing investments not only in very large datacenters, but also in large-scale software infrastructure and operational expertise required to run them. ---- who can be cloud provider
James Hamilton’s estimates [23] that very large datacenters (tens of thousands of computers) can purchase hardware, network bandwidth, and power for 1/5 to 1/7 the prices offered to a medium-sized (hundreds or thousands of computers) datacenter. Further, the fixed costs of software development and deployment can be amortized over many more machines.
why intel does not provide cloud computing? It's all about *computing*it’s cheaper to ship data over fiber optic cables than to ship electricity over high-voltage transmission lines.
the cost/benefit analysis must weigh the cost of moving large datasets into the cloud against the benefit of potential speedup in the data analysis.
Real world estimates of server utilization in datacenters range from 5% to 20%
Elastic is the key feature of Cloud ComputingIf new technologies or pricing plans become available to a cloud vendor, existing applications and customers can potentially benefit from them immediately, without incurring a capital expense.
A second opportunity is to find other reasons to make it attractive to keep data in the cloud, for once data is in the cloud for any reason it may no longer be a bottleneck and may enable new services that could drive the purchase of Cloud Computing cycles.
One of the difficult challenges in Cloud Computing is removing errors in these very large scale distributed systems. A common occurrence is that these bugs cannot be reproduced in smaller configurations, so the debugging must occur at scale in the production datacenters.
A fast and easy-to-use snapshot/restart tool might further encourage conservation of computing resources.
the licensing model for commercial software is not a good match to Utility Computing.